Single plate CCD cameras, in which a color filter is provided for each pixel to obtain image data on each of the RGB colors for each pixel, are widely used. In image capturing using such a CCD camera, an image which has passed through an optical antialias filter is detected by light receiving elements having color filters, whereby RGB image signals are obtained. An image capturing process can be modeled as shown in FIG. 1. Specifically, an image of a scene for image capturing passes through an optical antialias filter 1, and then enters a color filter array (CFA) 2, where the image is converted into RGB image signals. Thus, after being blurred to some extent by means of an optical system, the RGB image signals are sampled as RGB mosaic images.
Here, many of the single plate image capturing devices employ a Bayer-pattern CFA, where RGB image capturing pixels are arranged in a matrix, as shown in FIG. 2. An image obtained using an image capturing device (for example, a CCD) which employs a Bayer CFA is a mosaic image, which has green data for a half of the entire pixels, red data for a quarter of the entire pixels, and blue data for a quarter of the entire pixels. Therefore, in order to obtain a normal captured color image based on a mosaic image obtained using an image capturing device, restoration of the data on a missing pixel is required. This process for restoration is referred to as demosaicing.
Demosaicing, however, has problems, including, for example, false color and/or zipper noise in a restored image, which must be suppressed, and reduction of sharpness of a restored image, which must be enhanced. False color refers to a phenomenon in which a color which does not exist in an original image is produced in a restored image. Zipper noise refers to a phenomenon in which high frequency component is decreased, producing artifact in the form of a broken line.
A general demosaicing method includes low pass filtering. In demosaicing by means of filtering, fineness of and occurrence of false color in a restored image retain trade-off relationship.
In connection with the above, U.S. Pat. No. 5,629,734 discloses “Adaptive Color Plane Interpolation (ACPI)”; U.S. Pat. No. 5,373,322 discloses “Gradient Based Interpolation (GBI)”, and U.S. Pat. No. 4,642,678 discloses “Constant Hue-Based Interpolation (CHBI)”.
According to ACPI disclosed in U.S. Pat. No. 5,629,734, green data is interpolated by adding a secondary gradient of red or blue pixel values to the average of the adjacent pixel values, and red or blue data is interpolated by adding a secondary gradient of green pixel values to the average of the adjacent pixel values.
According to GBI disclosed in U.S. Pat. No. 5,373,322, green data is interpolated using the average of the adjacent pixel values, and red and blue data is interpolated by adding a green pixel value to a differential average of blue and green or red and green pixel values.
According to CHBI disclosed in U.S. Pat. No. 4,642,678, green data is interpolated using the average of the adjacent pixel values, and red and blue data is interpolated by multiplying the average of R/G or B/G by a green pixel value.
According to “Demosaicing Methods for Bayer Color Arrays,” (by R. Ramanath, W. E. Snyder, G. L. Bilbro, Journal of Electronic Imaging, Vol. 11, No. 3, pp. 306-315, 2002), performances attained using those prevailing methods are compared, with a conclusion obtained that the ACPI exhibits the highest performance.
ACPI, however, is problematic in that, although it can provide a fine image with less false color or zipper noise, isolated points become more common. The present invention advantageously achieve restoration of a more suitable image.